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A survey of in-spin transfer torque MRAM computing

  • Hao Cai
  • , Bo Liu
  • , Juntong Chen
  • , Lirida Naviner
  • , Yongliang Zhou
  • , Zhen Wang
  • , Jun Yang
  • Southeast University
  • Ltd.

Résultats de recherche: Contribution à un journalArticle de révisionRevue par des pairs

33 Citations (Scopus)

Résumé

In traditional von Neumann computing architectures, the essential transfer of data between the processor and memory hierarchies limits the computational efficiency of next-generation system-on-a-chip. The emerging in-memory computing (IMC) approach addresses this issue and facilitates the movement of significant data and rapid computations. Among the different memory types, intrinsic energy efficiency is demonstrated by in-magnetic random access memory (MRAM) computing with a low-power spintronic magnetic tunnel junction device and hybrid integration at an advanced complementary metal-oxide semiconductor node. This study reviews state-of-the-art techniques for managing IMC with an emphasis on spin-transfer torque-MRAM computing via design schemes at the bit-cell, circuit, and system levels. In addition, this study presents effective design techniques and potential challenges and demonstrates the existing limitations of in-MRAM computing and potential methods for overcoming these issues. This study also considers the design technology co-optimization from the IMC perspective.

langue originaleAnglais
Numéro d'article160402
journalScience China Information Sciences
Volume64
Numéro de publication6
Les DOIs
étatPublié - 1 juin 2021

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  1. SDG 7 - Énergie abordable et propre
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